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Ecohydrology Towards Integrative Ecosystem Modeling: A Review Setyono Hari Adi
Jurnal Sumberdaya Lahan Vol 11, No 2 (2017)
Publisher : Indonesian Center for Agriculture Land Resource Development

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21082/jsdl.v11n2.2017.67-76

Abstract

Keterkaitan antara air dan ekosistem sudah dikenal sejak lama, akan tetapi konsep ekohidrologi baru saja diperkenalkan sejak tiga dekade yang lalu. Konsep ini memperluas tema penelitian di bidang hidrologi dengan mengintegrasikan parameter ekologi ke dalam proses pemodelannya. Artikel ini ditulis untuk mengidentifikasi tren penelitian di bidang hidrologi selama satu dekade terakhir (2004-2015), dengan tujuan utama untuk mencari kesenjangan antara penelitian hidrologi dan ekologi ke arah pemodelan ekosistem yang terintegrasi. Data dari artikel-artikel bersitasi tinggi di tiga jurnal publikasi internasional di bidang sumber daya air menunjukkan bahwa hanya 10% dari total artikel yang direview mengintegrasikan parameter ekologi secara kuantitatif. Rendahnya persentase integrasi ekologi dalam penelitian di bidang sumber daya air disebabkan oleh tiga kesenjangan ilmiah, meliputi: (1) kesenjangan isu, dimana isu sumber daya air diperlakukan sebagai variabel empiris utama; (2) kesenjangan model, dimana air merupakan satu-satunya parameter yang dipertimbangkan dalam pemodelan; dan (3) kesenjangan data, yang terfokus pada permasalahan ketersediaan data ekologi untuk analisis. Tiga rekomendasi terkait dengan kesenjangan ilmiah ini meliputi: (1) memperkuat konsep ekohidrologi dengan memandang air adalah bagian tidak terpisahkan dari ekosistem bumi yang saling terkait, (2) mendorong integrasi parameter ekologi ke dalam pemodelan hidrologi, dan (3) pengembangan teknik peningkatan skala (resolusi) data yang terintegrasi dengan analisis ketidaktentuan.
PEDOTRANSFER FUNCTIONS FOR DIGITAL SOIL MAPPING IN TROPICAL REGION: A CASE STUDY OF DIGITAL SOIL MAPPING OF SOIL CARBON AND NITROGEN IN WEST JAVA, INDONESIA Setyono Hari Adi
Widyariset Vol 3, No 2 (2017): Widyariset
Publisher : Pusbindiklat - LIPI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1085.542 KB) | DOI: 10.14203/widyariset.3.2.2017.107-118

Abstract

Pedotransfer functions (PTFs) for the tropical region were developed to model topsoil total carbon and nitrogen variations, by using input parameters of Digital Elevation Model—DEM, Normalized Difference Vegetation Index—NDVI and bioclimatic variables. Puerto Rico dataset was used to develop the model, while West Java, Indonesia was chosen for the model application. Using 22 input parameters derived from the three soil forming factors (relief, vegetation, and climate), the PTF could explain 71% and 66% of the soil total carbon and nitrogen variations, while comparable results were obtained from reduced input parameters (RMSE 3.12% and 0.05% for topsoil total carbon and nitrogen, respectively). This result suggests that application of PTFs to model soil properties variation, especially in the tropical region, could be used to generate reliable pre-assessment information to support decision making in the land productivity improvement plan.
PEDOTRANSFER FUNCTIONS FOR DIGITAL SOIL MAPPING IN TROPICAL REGION: A CASE STUDY OF DIGITAL SOIL MAPPING OF SOIL CARBON AND NITROGEN IN WEST JAVA, INDONESIA Setyono Hari Adi
Widyariset Vol 3, No 2 (2017): Widyariset
Publisher : Pusbindiklat - LIPI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1085.542 KB) | DOI: 10.14203/widyariset.3.2.2017.107-118

Abstract

Pedotransfer functions (PTFs) for the tropical region were developed to model topsoil total carbon and nitrogen variations, by using input parameters of Digital Elevation Model—DEM, Normalized Difference Vegetation Index—NDVI and bioclimatic variables. Puerto Rico dataset was used to develop the model, while West Java, Indonesia was chosen for the model application. Using 22 input parameters derived from the three soil forming factors (relief, vegetation, and climate), the PTF could explain 71% and 66% of the soil total carbon and nitrogen variations, while comparable results were obtained from reduced input parameters (RMSE 3.12% and 0.05% for topsoil total carbon and nitrogen, respectively). This result suggests that application of PTFs to model soil properties variation, especially in the tropical region, could be used to generate reliable pre-assessment information to support decision making in the land productivity improvement plan.
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